Socioeconomic distress and health status: the urban-rural dichotomy of services utilization for people with sickle cell disorder in North Carolina

J Rural Health. 2000 Winter;16(1):43-55. doi: 10.1111/j.1748-0361.2000.tb00435.x.

Abstract

Research on sickle cell disorder has not focused attention on the socioeconomic background and geographic distribution of people with the disease. This study examines 1,189 persons with sickle cell disorder in North Carolina during 1991 to 1995. Three indices were developed using clients' medical, psychosocial and socioeconomic characteristics for the purpose of analyzing the urban-rural difference in treatment for sickle cell disease. The study observed a wide disparity in these indices between urban and rural population groups. Also, differences were observed in the utilization of services and clients' health status. The findings suggest that utilization of services is directly related to socioeconomic condition facing clients and clinic distance from clients. They further suggest that people in rural areas who have high distress levels and are far from clinics have limited access to health care. The limited availability of medical and health care in rural areas, as well as other support systems calls for an increase in community based healthcare services. These findings should be of particular interest to the state level sickle cell disorder program in North Carolina and other areas with a large rural population. Enhanced support for all persons with sickle cell disorder in North Carolina, particularly those in rural areas, is critical.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adolescent
  • Adult
  • Anemia, Sickle Cell / therapy*
  • Child
  • Child, Preschool
  • Community Health Services / statistics & numerical data*
  • Female
  • Health Services Accessibility / statistics & numerical data
  • Humans
  • Infant
  • Male
  • North Carolina / epidemiology
  • Poverty / statistics & numerical data
  • Regression Analysis
  • Rural Health / statistics & numerical data*
  • Sickness Impact Profile
  • Social Class*
  • Urban Health / statistics & numerical data*